Whole Exome Sequencing Identified Sixty-Five Coding Mutations in Four

Total Page:16

File Type:pdf, Size:1020Kb

Whole Exome Sequencing Identified Sixty-Five Coding Mutations in Four www.nature.com/scientificreports OPEN Whole exome sequencing identifed sixty-fve coding mutations in four neuroblastoma tumors Received: 30 September 2016 Aubrey L. Miller1, Patrick L. Garcia1, Joseph G. Pressey2,8, Elizabeth A. Beierle3, David R. Accepted: 20 November 2017 Kelly4,5, David K. Crossman6, Leona N. Council4,7, Richard Daniel5, Raymond G. Watts2,9, Published: xx xx xxxx Stuart L. Cramer2,10 & Karina J. Yoon1 Neuroblastoma is a pediatric tumor characterized by histologic heterogeneity, and accounts for ~15% of childhood deaths from cancer. The fve-year survival for patients with high-risk stage 4 disease has not improved in two decades. We used whole exome sequencing (WES) to identify mutations present in three independent high-risk stage 4 neuroblastoma tumors (COA/UAB-3, COA/UAB -6 and COA/ UAB -8) and a stage 3 tumor (COA/UAB-14). Among the four tumors WES analysis identifed forty- three mutations that had not been reported previously, one of which was present in two of the four tumors. WES analysis also corroborated twenty-two mutations that were reported previously. No single mutation occurred in all four tumors or in all stage 4 tumors. Three of the four tumors harbored genes with CADD scores ≥20, indicative of mutations associated with human pathologies. The average depth of coverage ranged from 39.68 to 90.27, with >99% sequences mapping to the genome. In summary, WES identifed sixty-fve coding mutations including forty-three mutations not reported previously in primary neuroblastoma tumors. The three stage 4 tumors contained mutations in genes encoding protein products that regulate immune function or cell adhesion and tumor cell metastasis. Neuroblastoma (NB) is an embryonal tumor arising from neural crest cells of the sympathetic nervous system1. It is the most common extracranial solid tumor of children, and accounts for ~15% of all childhood cancer deaths. Treatment of children with high-risk disease has been a major challenge in pediatric oncology. Patients less than 18 months of age with low risk disease attain cancer-free status with tumor resection alone or without interven- tion, due to spontaneous tumor regression2. In contrast, patients older than 18 months of age who have high-risk factors such as MYCN amplifcation, bilateral disease, and near-diploid or near-tetraploid karyotype ofen relapse afer initial treatment and remission, with an almost uniformly fatal outcome3–6. Te new International Neuroblastoma Risk Group (INRG) Staging System has taken advantage of recent advances in medical imaging and biomolecular diagnostics to establish a consensus for risk stratification5. Te criteria for classifcation include stage, age, histology, tumor grade and MYCN gene copy number. Criteria for high-risk NB include age greater than 18 months, stage 2 or 3 with MYCN amplifcation, and unfavorable histology6. Genetic abnormalities associated with high-risk stage 4 NB include hemizygous deletions of the q arm of chromosome 11 (up to 62.5% of tumors) and of the p arm of chromosome 1 (25–35% of tumors), and MYCN amplifcation in ~25% of tumors3,4,7–12. Gains in the long arm of chromosome 17 (17q21–17qter) is one of the most frequent genetic alterations in NB, occurring 50–70% of all high-risk tumors3,4. Recent advances in next-generation sequencing technology and a collaboration between The Pediatric Tumor Bank and Tumorgraf Development Initiative at Children’s of Alabama and the University of Alabama 1Department of Pharmacology and Toxicology, University of Alabama at Birmingham, Birmingham, AL, USA. 2Department of Pediatrics, University of Alabama at Birmingham, Birmingham, AL, USA. 3Department of Surgery, University of Alabama at Birmingham, Birmingham, AL, USA. 4Department of Pathology, University of Alabama at Birmingham, Birmingham, AL, USA. 5Department of Pathology and Laboratory Medicine, Children’s of Alabama, Birmingham, AL, USA. 6Department of Genetics, University of Alabama at Birmingham, Birmingham, AL, USA. 7The Birmingham Veterans Administration Medical Center, Birmingham, AL, USA. 8Present address: Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA. 9Present address: Department of Pediatrics, LSUHSC School of Medicine, New Orleans, LA, USA. 10Present address: Palmetto Health Children’s Hospital, Columbia, SC, USA. Correspondence and requests for materials should be addressed to K.J.Y. (email: [email protected]) SCIENTIFIC REPORTS | 7: 17787 | DOI:10.1038/s41598-017-17162-y 1 www.nature.com/scientificreports/ Tumor INRG* Diferentiation MYCN >18 Tumor ID Type Stage Staging (Grade) amplifed months COA/ UAB-3 NB 4 M Poor Yes Yes COA/ UAB-6 NB 4 M Poor Yes Yes COA/ UAB-8 NB 4 M Poor No Yes COA/ UAB-14 NB 3 L2 Poor No No Table 1. Clinical characteristics associated with four primary neuroblastoma tumors. *INRG: International Neuroblastoma Risk Group. COA/UAB-3 COA/UAB-6 COA/UAB-8 COA/UAB-14 Not Not Not Not Variants Types reported Reported reported Reported reported Reported reported Reported Nonsynonymous coding1 12 3 6 7 4 1 13 8 Nonsynonymous start2 Splice site acceptor3 1 1 1 Splice site donor3 Start gained4 2 1 1 1 Start lost4 1 Stop gained5 2 1 Stop lost5 TOATL # VARIANTS 16 3 7 8 5 2 16 9 TOTAL # GENES 15 3 7 8 4 2 15 9 Table 2. Summary of variants (mutations) types for all mutations identifed in four neuroblastoma tumors. 1Mutation of a single nucleotide, resulting in an amino acid change in the encoded protein; may afect phenotype66. 2Mutation that occurs in a coding region, at start site. 3Mutation that changes nucleotides in genomic loci where splicing takes place. 4Mutation that generates a new translation initiation codon in the 5′UTR, or that results in the loss of an initiation codon. Start site loss may result in the loss of protein product. 5Mutation that changes the sequence of a codon to create or remove a stop codon (UAA, UAG, UGA). at Birmingham (COA-UAB) facilitated performing whole exome sequencing (WES) to analyze four recently acquired neuroblastoma specimens. Te goals of the study were to sequence the exome of these primary tumors using Whole Exome sequencing to identify mutations, to generate CADD (Combined Annotation Dependent Depletion) scores as a measure of predicted pathogenicity of mutated gene products, and to compare WES data of the stage 3 tumor with the three stage 4 tumors. Results Clinical characteristics associated with primary neuroblastoma tumors in this study. Primary tumors were received from patients who underwent surgery as standard of care at Children’s of Alabama Hospital (Table 1). Tumors were obtained from patients diagnosed with intermediate (COA/UAB-14) or high-risk dis- ease (COA/UAB-3, COA/UAB-6, COA/UAB-8). Tumors COA/UAB-3 and COA/UAB-6 were MYCN amplifed. Tumor specimens COA/UAB-3, /UAB-6, and /UAB-8 were obtained from patients older than 18 months, and had high-risk characteristics that included unfavorable histology and MYCN amplifcation. WES identifed 43 mutations not reported previously in four neuroblastoma tumors. WES analysis revealed that each tumor harbored between seven and twenty-fve mutations (Table 2). Te average of 16 mutations per tumor is consistent with previous reports of 12–18 mutations per tumor13,14. Te four tumors harbored 43 mutations not previously observed in NB tumors in the dbSNP database (version 138), as well as 22 mutations reported previously to be present in other tumor types15. Tose 43 mutations are in bold in Tables 2–6. In Tables 3–6, ‘p’ in the third column of each Table identifes the amino acid substitution and position; ‘c’ in this column identifes the nucleotide substitution and position. While no mutation was common to all four tumors, one of the mutations in the RHPN2 gene was present in two of the four tumors examined: the mutation in this gene (Rhophilin, Rho GTPase Binding Protein 2) was present at nucleotide 217 (G > A encoding Val73Met) in COA/UAB-3 and COA/UAB-8 tumors (Tables 3–5). RHPN2 contributes to actin cytoskeleton organization, an organelle that regulates cell motility16,17. A second mutation introducing a start site of RHPN2 gene also occurred in tumors COA/UAB-3 and COA/UAB-8. Te location of the introduced start site at the intron-exon bound- ary suggests that this mutation is unlikely to alter the protein product in tumors COA/UAB-3 and COA/UAB- 8. A genome-wide association study (GWAS) found that a region containing RHPN2 has been associated with increased susceptibility to colorectal cancer18. Genes encoding MUC4 and ADAM21 also contained mutations in two of the four tumors, but at diferent loci. Mucin 4 (MUC4), a transmembrane mucin expressed predominantly by normal epithelial cells, is involved in cell diferentiation, inhibition of cell adhesion, and cell migration19–21. MUC4 protein is thought to contribute SCIENTIFIC REPORTS | 7: 17787 | DOI:10.1038/s41598-017-17162-y 2 www.nature.com/scientificreports/ Mutation Ch#+ Gene Mutation type Known functions/pathways of normal gene product 1* TCEB3 p.Ala18Val/c.53 C > T Missense Activates RNA polymerase II elongation 1* TOE1 p.Ala2Val/c.5 C > T Missense Inhibits cell growth and cell cycle progression 1 MAEL p.Tyr344Asn/c.1030 T > A Missense Spermatogenesis 1 SELL Start gained Mediates adhesion 2* WDR35 p.Ala1018Asp/c.3053 C > A Missense Promotes CASP3 activation 2* COL4A4 p.Gly645*/c.1933G > T Nonsense Major structural component of basement membrane 3 MUC4 p.Ala1646Tr/c.4936 G > A Missense Plays a role in tumor progression; anti-adhesive properties 6 CLIC5 p.Gln50His/c.150 G > T Missense Chloride ion transport 6 FOXO3 p.Glu17Val/c.50 A > T Missense Apoptosis; transcriptional activator 13 ITM2B p.Ala153Val/c.458 C > T Missense Processing beta-amyloids A4 precursor protein (APP) 14 RNASE4 p.Cys85Phe/c.254 G > T Missense Degrades RNA 14 ADAM21 p.Pro40Leu/c.119 C > T Missense Adhesion protein involved in sperm maturation; epithelial cell function 17 ACADVL p.Phe266Leu/c.798 C > A Missense Mitochondrial fatty acid beta-oxidation 19 GIPR p.His115Asn/c.343 C > A Missense Pathogenesis of diabetes Binds to and activates GTP-Rho, negatively regulates stress fber 19 RHPN2 p.Val73Met/c.217 G > A Missense formation and facilitates motility of many cell types including T and B cells.
Recommended publications
  • Supplementary Data
    Figure 2S 4 7 A - C 080125 CSCs 080418 CSCs - + IFN-a 48 h + IFN-a 48 h + IFN-a 72 h 6 + IFN-a 72 h 3 5 MRFI 4 2 3 2 1 1 0 0 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 7 B 13 080125 FBS - D 080418 FBS - + IFN-a 48 h 12 + IFN-a 48 h + IFN-a 72 h + IFN-a 72 h 6 080125 FBS 11 10 5 9 8 4 7 6 3 MRFI 5 4 2 3 2 1 1 0 0 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 Molecule Molecule FIGURE 4S FIGURE 5S Panel A Panel B FIGURE 6S A B C D Supplemental Results Table 1S. Modulation by IFN-α of APM in GBM CSC and FBS tumor cell lines. Molecule * Cell line IFN-α‡ HLA β2-m# HLA LMP TAP1 TAP2 class II A A HC§ 2 7 10 080125 CSCs - 1∞ (1) 3 (65) 2 (91) 1 (2) 6 (47) 2 (61) 1 (3) 1 (2) 1 (3) + 2 (81) 11 (80) 13 (99) 1 (3) 8 (88) 4 (91) 1 (2) 1 (3) 2 (68) 080125 FBS - 2 (81) 4 (63) 4 (83) 1 (3) 6 (80) 3 (67) 2 (86) 1 (3) 2 (75) + 2 (99) 14 (90) 7 (97) 5 (75) 7 (100) 6 (98) 2 (90) 1 (4) 3 (87) 080418 CSCs - 2 (51) 1 (1) 1 (3) 2 (47) 2 (83) 2 (54) 1 (4) 1 (2) 1 (3) + 2 (81) 3 (76) 5 (75) 2 (50) 2 (83) 3 (71) 1 (3) 2 (87) 1 (2) 080418 FBS - 1 (3) 3 (70) 2 (88) 1 (4) 3 (87) 2 (76) 1 (3) 1 (3) 1 (2) + 2 (78) 7 (98) 5 (99) 2 (94) 5 (100) 3 (100) 1 (4) 2 (100) 1 (2) 070104 CSCs - 1 (2) 1 (3) 1 (3) 2 (78) 1 (3) 1 (2) 1 (3) 1 (3) 1 (2) + 2 (98) 8 (100) 10 (88) 4 (89) 3 (98) 3 (94) 1 (4) 2 (86) 2 (79) * expression of APM molecules was evaluated by intracellular staining and cytofluorimetric analysis; ‡ cells were treatead or not (+/-) for 72 h with 1000 IU/ml of IFN-α; # β-2 microglobulin; § β-2 microglobulin-free HLA-A heavy chain; ∞ values are indicated as ratio between the mean of fluorescence intensity of cells stained with the selected mAb and that of the negative control; bold values indicate significant MRFI (≥ 2).
    [Show full text]
  • New Approaches to Functional Process Discovery in HPV 16-Associated Cervical Cancer Cells by Gene Ontology
    Cancer Research and Treatment 2003;35(4):304-313 New Approaches to Functional Process Discovery in HPV 16-Associated Cervical Cancer Cells by Gene Ontology Yong-Wan Kim, Ph.D.1, Min-Je Suh, M.S.1, Jin-Sik Bae, M.S.1, Su Mi Bae, M.S.1, Joo Hee Yoon, M.D.2, Soo Young Hur, M.D.2, Jae Hoon Kim, M.D.2, Duck Young Ro, M.D.2, Joon Mo Lee, M.D.2, Sung Eun Namkoong, M.D.2, Chong Kook Kim, Ph.D.3 and Woong Shick Ahn, M.D.2 1Catholic Research Institutes of Medical Science, 2Department of Obstetrics and Gynecology, College of Medicine, The Catholic University of Korea, Seoul; 3College of Pharmacy, Seoul National University, Seoul, Korea Purpose: This study utilized both mRNA differential significant genes of unknown function affected by the display and the Gene Ontology (GO) analysis to char- HPV-16-derived pathway. The GO analysis suggested that acterize the multiple interactions of a number of genes the cervical cancer cells underwent repression of the with gene expression profiles involved in the HPV-16- cancer-specific cell adhesive properties. Also, genes induced cervical carcinogenesis. belonging to DNA metabolism, such as DNA repair and Materials and Methods: mRNA differential displays, replication, were strongly down-regulated, whereas sig- with HPV-16 positive cervical cancer cell line (SiHa), and nificant increases were shown in the protein degradation normal human keratinocyte cell line (HaCaT) as a con- and synthesis. trol, were used. Each human gene has several biological Conclusion: The GO analysis can overcome the com- functions in the Gene Ontology; therefore, several func- plexity of the gene expression profile of the HPV-16- tions of each gene were chosen to establish a powerful associated pathway, identify several cancer-specific cel- cervical carcinogenesis pathway.
    [Show full text]
  • The Rnase H-Like Superfamily: New Members, Comparative Structural Analysis and Evolutionary Classification Karolina A
    4160–4179 Nucleic Acids Research, 2014, Vol. 42, No. 7 Published online 23 January 2014 doi:10.1093/nar/gkt1414 The RNase H-like superfamily: new members, comparative structural analysis and evolutionary classification Karolina A. Majorek1,2,3,y, Stanislaw Dunin-Horkawicz1,y, Kamil Steczkiewicz4, Anna Muszewska4,5, Marcin Nowotny6, Krzysztof Ginalski4 and Janusz M. Bujnicki1,3,* 1Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology, ul. Ks. Trojdena 4, PL-02-109 Warsaw, Poland, 2Department of Molecular Physiology and Biological Physics, University of Virginia, 1340 Jefferson Park Avenue, Charlottesville, VA USA-22908, USA, 3Bioinformatics Laboratory, Institute of Molecular Biology and Biotechnology, Adam Mickiewicz University, Umultowska 89, PL-61-614 Poznan, Poland, 4Laboratory of Bioinformatics and Systems Biology, Centre of New Technologies, University of Warsaw, Zwirki i Wigury 93, PL-02-089 Warsaw, Poland, 5Institute of Biochemistry and Biophysics PAS, Pawinskiego 5A, PL-02-106 Warsaw, Poland and 6Laboratory of Protein Structure, International Institute of Molecular and Cell Biology, ul. Ks. Trojdena 4, PL-02-109 Warsaw, Poland Received September 23, 2013; Revised December 12, 2013; Accepted December 26, 2013 ABSTRACT revealed a correlation between the orientation of Ribonuclease H-like (RNHL) superfamily, also called the C-terminal helix with the exonuclease/endo- the retroviral integrase superfamily, groups together nuclease function and the architecture of the numerous enzymes involved in nucleic acid metab- active site. Our analysis provides a comprehensive olism and implicated in many biological processes, picture of sequence-structure-function relation- including replication, homologous recombination, ships in the RNHL superfamily that may guide func- DNA repair, transposition and RNA interference.
    [Show full text]
  • Stelios Pavlidis3, Matthew Loza3, Fred Baribaud3, Anthony
    Supplementary Data Th2 and non-Th2 molecular phenotypes of asthma using sputum transcriptomics in UBIOPRED Chih-Hsi Scott Kuo1.2, Stelios Pavlidis3, Matthew Loza3, Fred Baribaud3, Anthony Rowe3, Iaonnis Pandis2, Ana Sousa4, Julie Corfield5, Ratko Djukanovic6, Rene 7 7 8 2 1† Lutter , Peter J. Sterk , Charles Auffray , Yike Guo , Ian M. Adcock & Kian Fan 1†* # Chung on behalf of the U-BIOPRED consortium project team 1Airways Disease, National Heart & Lung Institute, Imperial College London, & Biomedical Research Unit, Biomedical Research Unit, Royal Brompton & Harefield NHS Trust, London, United Kingdom; 2Department of Computing & Data Science Institute, Imperial College London, United Kingdom; 3Janssen Research and Development, High Wycombe, Buckinghamshire, United Kingdom; 4Respiratory Therapeutic Unit, GSK, Stockley Park, United Kingdom; 5AstraZeneca R&D Molndal, Sweden and Areteva R&D, Nottingham, United Kingdom; 6Faculty of Medicine, Southampton University, Southampton, United Kingdom; 7Faculty of Medicine, University of Amsterdam, Amsterdam, Netherlands; 8European Institute for Systems Biology and Medicine, CNRS-ENS-UCBL, Université de Lyon, France. †Contributed equally #Consortium project team members are listed under Supplementary 1 Materials *To whom correspondence should be addressed: [email protected] 2 List of the U-BIOPRED Consortium project team members Uruj Hoda & Christos Rossios, Airways Disease, National Heart & Lung Institute, Imperial College London, UK & Biomedical Research Unit, Biomedical Research Unit, Royal
    [Show full text]
  • A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
    Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated.
    [Show full text]
  • PROTEOMIC ANALYSIS of HUMAN URINARY EXOSOMES. Patricia
    ABSTRACT Title of Document: PROTEOMIC ANALYSIS OF HUMAN URINARY EXOSOMES. Patricia Amalia Gonzales Mancilla, Ph.D., 2009 Directed By: Associate Professor Nam Sun Wang, Department of Chemical and Biomolecular Engineering Exosomes originate as the internal vesicles of multivesicular bodies (MVBs) in cells. These small vesicles (40-100 nm) have been shown to be secreted by most cell types throughout the body. In the kidney, urinary exosomes are released to the urine by fusion of the outer membrane of the MVBs with the apical plasma membrane of renal tubular epithelia. Exosomes contain apical membrane and cytosolic proteins and can be isolated using differential centrifugation. The analysis of urinary exosomes provides a non- invasive means of acquiring information about the physiological or pathophysiological state of renal cells. The overall objective of this research was to develop methods and knowledge infrastructure for urinary proteomics. We proposed to conduct a proteomic analysis of human urinary exosomes. The first objective was to profile the proteome of human urinary exosomes using liquid chromatography-tandem spectrometry (LC- MS/MS) and specialized software for identification of peptide sequences from fragmentation spectra. We unambiguously identified 1132 proteins. In addition, the phosphoproteome of human urinary exosomes was profiled using the neutral loss scanning acquisition mode of LC-MS/MS. The phosphoproteomic profiling identified 19 phosphorylation sites corresponding to 14 phosphoproteins. The second objective was to analyze urinary exosomes samples isolated from patients with genetic mutations. Polyclonal antibodies were generated to recognize epitopes on the gene products of these genetic mutations, NKCC2 and MRP4. The potential usefulness of urinary exosome analysis was demonstrated using the well-defined renal tubulopathy, Bartter syndrome type I and using the single nucleotide polymorphism in the ABCC4 gene.
    [Show full text]
  • Transcriptomic Analysis of Native Versus Cultured Human and Mouse Dorsal Root Ganglia Focused on Pharmacological Targets Short
    bioRxiv preprint doi: https://doi.org/10.1101/766865; this version posted September 12, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. Transcriptomic analysis of native versus cultured human and mouse dorsal root ganglia focused on pharmacological targets Short title: Comparative transcriptomics of acutely dissected versus cultured DRGs Andi Wangzhou1, Lisa A. McIlvried2, Candler Paige1, Paulino Barragan-Iglesias1, Carolyn A. Guzman1, Gregory Dussor1, Pradipta R. Ray1,#, Robert W. Gereau IV2, # and Theodore J. Price1, # 1The University of Texas at Dallas, School of Behavioral and Brain Sciences and Center for Advanced Pain Studies, 800 W Campbell Rd. Richardson, TX, 75080, USA 2Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine # corresponding authors [email protected], [email protected] and [email protected] Funding: NIH grants T32DA007261 (LM); NS065926 and NS102161 (TJP); NS106953 and NS042595 (RWG). The authors declare no conflicts of interest Author Contributions Conceived of the Project: PRR, RWG IV and TJP Performed Experiments: AW, LAM, CP, PB-I Supervised Experiments: GD, RWG IV, TJP Analyzed Data: AW, LAM, CP, CAG, PRR Supervised Bioinformatics Analysis: PRR Drew Figures: AW, PRR Wrote and Edited Manuscript: AW, LAM, CP, GD, PRR, RWG IV, TJP All authors approved the final version of the manuscript. 1 bioRxiv preprint doi: https://doi.org/10.1101/766865; this version posted September 12, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.
    [Show full text]
  • Identification and Functional Analysis of Novel Genes Associated with Inherited Bone Marrow Failure Syndromes
    Identification and Functional Analysis of Novel Genes Associated with Inherited Bone Marrow Failure Syndromes by Anna Matveev A thesis submitted in conformity with the requirements for the degree of Master of Science Institute of Medical Science University of Toronto © Copyright by Anna Matveev 2020 Abstract Identification and Functional Analysis of Novel Genes Associated with Inherited Bone Marrow Failure Syndromes Anna Matveev Master of Science Institute of Medical Science University of Toronto 2020 Inherited bone marrow failure syndromes are multisystem-disorders that affect development of hematopoietic system. One of IBMFSs is Shwachman-Diamond-syndrome and about 80-90% of patients have mutations in the Shwachman-Bodian-Diamond-Syndrome gene. To unravel the genetic cause of the disease in the remaining 10-20% of patients, we performed WES as well as SNP-genotyping in families with SDS-phenotype and no mutations in SBDS. The results showed a region of homozygosity in chromosome 5p-arm DNAJC21 is in this region. Western blotting revealed reduced/null protein in patient. DNAJC21-homolog in yeast has been shown facilitating the release of the Arx1/Alb1 heterodimer from pre-60S.To investigate the cellular functions of DNAJC21 we knocked-down it in HEK293T-cells. We observed a high-level of ROS, which led to reduced cell proliferation. Our data indicate that mutations in DNAJC21 contribute to SDS. We hypothesize that DNAJC21 related ribosomal defects lead to increased levels of ROS therefore altering development and maturation of hematopoietic cells. ii Acknowledgments I would like to take this opportunity to extend my deepest gratitude to everyone who has helped me throughout my degree.
    [Show full text]
  • Renal Cell Neoplasms Contain Shared Tumor Type–Specific Copy Number Variations
    The American Journal of Pathology, Vol. 180, No. 6, June 2012 Copyright © 2012 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ajpath.2012.01.044 Tumorigenesis and Neoplastic Progression Renal Cell Neoplasms Contain Shared Tumor Type–Specific Copy Number Variations John M. Krill-Burger,* Maureen A. Lyons,*† The annual incidence of renal cell carcinoma (RCC) has Lori A. Kelly,*† Christin M. Sciulli,*† increased steadily in the United States for the past three Patricia Petrosko,*† Uma R. Chandran,†‡ decades, with approximately 58,000 new cases diag- 1,2 Michael D. Kubal,§ Sheldon I. Bastacky,*† nosed in 2010, representing 3% of all malignancies. Anil V. Parwani,*†‡ Rajiv Dhir,*†‡ and Treatment of RCC is complicated by the fact that it is not a single disease but composes multiple tumor types with William A. LaFramboise*†‡ different morphological characteristics, clinical courses, From the Departments of Pathology* and Biomedical and outcomes (ie, clear-cell carcinoma, 82% of RCC ‡ Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania; cases; type 1 or 2 papillary tumors, 11% of RCC cases; † the University of Pittsburgh Cancer Institute, Pittsburgh, chromophobe tumors, 5% of RCC cases; and collecting § Pennsylvania; and Life Technologies, Carlsbad, California duct carcinoma, approximately 1% of RCC cases).2,3 Benign renal neoplasms are subdivided into papillary adenoma, renal oncocytoma, and metanephric ade- Copy number variant (CNV) analysis was performed on noma.2,3 Treatment of RCC often involves surgical resec- renal cell carcinoma (RCC) specimens (chromophobe, tion of a large renal tissue component or removal of the clear cell, oncocytoma, papillary type 1, and papillary entire affected kidney because of the relatively large size of type 2) using high-resolution arrays (1.85 million renal tumors on discovery and the availability of a life-sus- probes).
    [Show full text]
  • Prediction of Meiosis-Essential Genes Based Upon the Dynamic Proteomes Responsive to Spermatogenesis
    bioRxiv preprint doi: https://doi.org/10.1101/2020.02.05.936435; this version posted February 6, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. Prediction of meiosis-essential genes based upon the dynamic proteomes responsive to spermatogenesis Kailun Fang1,2,3,8, Qidan Li3,4,5,8, Yu Wei2,3,8, Jiaqi Shen6,8, Wenhui Guo3,4,5,7,8, Changyang Zhou2,3,8, Ruoxi Wu1, Wenqin Ying2, Lu Yu1,2, Jin Zi5, Yuxing Zhang3,4,5, Hui Yang2,3,9*, Siqi Liu3,4,5,9*, Charlie Degui Chen1,3,9* 1. State Key Laboratory of Molecular Biology, Shanghai Key Laboratory of Molecular Andrology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai 200031, China. 2. State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Research Center for Brain Science and Brain-Inspired Intelligence, Institute of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China. 3. University of the Chinese Academy of Sciences, Beijing 100049, China. 4. CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China. 5. BGI Genomics, BGI-Shenzhen, Shenzhen 518083, China. 6. United World College Changshu China, Jiangsu 215500, China. 7. Malvern College Qingdao, Shandong, 266109, China 8.
    [Show full text]
  • Evolution of the DAN Gene Family in Vertebrates
    bioRxiv preprint doi: https://doi.org/10.1101/794404; this version posted June 29, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. RESEARCH ARTICLE Evolution of the DAN gene family in vertebrates Juan C. Opazo1,2,3, Federico G. Hoffmann4,5, Kattina Zavala1, Scott V. Edwards6 1Instituto de Ciencias Ambientales y Evolutivas, Facultad de Ciencias, Universidad Austral de Chile, Valdivia, Chile. 2David Rockefeller Center for Latin American Studies, Harvard University, Cambridge, MA 02138, USA. 3Millennium Nucleus of Ion Channels-Associated Diseases (MiNICAD). 4 Department of Biochemistry, Molecular Biology, Entomology, and Plant Pathology, Mississippi State University, Mississippi State, 39762, USA. Cite as: Opazo JC, Hoffmann FG, 5 Zavala K, Edwards SV (2020) Institute for Genomics, Biocomputing, and Biotechnology, Mississippi State Evolution of the DAN gene family in University, Mississippi State, 39762, USA. vertebrates. bioRxiv, 794404, ver. 3 peer-reviewed and recommended by 6 PCI Evolutionary Biology. doi: Department of Organismic and Evolutionary Biology, Harvard University, 10.1101/794404 Cambridge, MA 02138, USA. This article has been peer-reviewed and recommended by Peer Community in Evolutionary Biology Posted: 29 June 2020 doi: 10.24072/pci.evolbiol.100104 ABSTRACT Recommender: Kateryna Makova The DAN gene family (DAN, Differential screening-selected gene Aberrant in Neuroblastoma) is a group of genes that is expressed during development and plays fundamental roles in limb bud formation and digitation, kidney formation and morphogenesis and left-right axis specification.
    [Show full text]
  • Cellular and Molecular Signatures in the Disease Tissue of Early
    Cellular and Molecular Signatures in the Disease Tissue of Early Rheumatoid Arthritis Stratify Clinical Response to csDMARD-Therapy and Predict Radiographic Progression Frances Humby1,* Myles Lewis1,* Nandhini Ramamoorthi2, Jason Hackney3, Michael Barnes1, Michele Bombardieri1, Francesca Setiadi2, Stephen Kelly1, Fabiola Bene1, Maria di Cicco1, Sudeh Riahi1, Vidalba Rocher-Ros1, Nora Ng1, Ilias Lazorou1, Rebecca E. Hands1, Desiree van der Heijde4, Robert Landewé5, Annette van der Helm-van Mil4, Alberto Cauli6, Iain B. McInnes7, Christopher D. Buckley8, Ernest Choy9, Peter Taylor10, Michael J. Townsend2 & Costantino Pitzalis1 1Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK. Departments of 2Biomarker Discovery OMNI, 3Bioinformatics and Computational Biology, Genentech Research and Early Development, South San Francisco, California 94080 USA 4Department of Rheumatology, Leiden University Medical Center, The Netherlands 5Department of Clinical Immunology & Rheumatology, Amsterdam Rheumatology & Immunology Center, Amsterdam, The Netherlands 6Rheumatology Unit, Department of Medical Sciences, Policlinico of the University of Cagliari, Cagliari, Italy 7Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow G12 8TA, UK 8Rheumatology Research Group, Institute of Inflammation and Ageing (IIA), University of Birmingham, Birmingham B15 2WB, UK 9Institute of
    [Show full text]